Design of automated negotiation mechanisms for decentralized heterogeneous machine scheduling

Lang, Fabian; Fink, Andréas; Brandt, Tobias

doi:10.1016/j.ejor.2015.06.058

Cited by 23 publications

(5 citation statements)

References 77 publications

(79 reference statements)

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“…Regarding the social welfare, we compare the ICA approach with a state-of-the-art decentralised negotiation mechanism inspired by simulated annealing (NMSA) proposed by Lang, Fink, and Brandt (2016) and two centralised approaches: genetic algorithm (GA) (Chaudhry and Elbadawi 2017) and particle swarm optimisation (PSO) (Fang and Lin 2013). Compared with NMSA, the relative growth rate (RGR) is applied to measure the promotion of social welfare.…”

Section: Experimentation and Results Analysismentioning

confidence: 99%

“…Lang and Fink (2015) summarised the requirements for negotiation protocol established on general heuristic optimisation algorithms. Fink and Homberger (2013) developed a decentralised approach using ant colony optimisation, and then negotiation mechanisms inspired by simulated annealing and random search evolutionary are proposed by Lang, Fink, and Brandt (2016) and Homberger and Fink (2017), respectively. These negotiation mechanisms are easy to be implemented and can generate solutions that agents agree on by exploiting the evolutionary properties of heuristic algorithms, while using iterative voting methods to protect the agents' preference information.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the centralised approach is applied under the assumption that the complete information is known by a central decision-maker. However, in many practical situations, agents are self-interested and may not be willing to disclose their private information (Klein et al 2003;Lang, Fink, and Brandt 2016), which makes the centralised approach inapplicable. Compared with the centralised approach, the decentralised decision-making approach deals with resource allocation problems through multiple decision-makers competing fully and making compromise resulting in some kind of equilibrium in case of asymmetric information (Schneeweiss 2003).…”

Section: Introductionmentioning

confidence: 99%

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An iterative combinatorialauctionmechanism formulti-agentparallel machinescheduling

Liu

Sun

Wang

et al. 2021

International Journal of Production Research

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This paper focuses on the multi-agent parallel machines scheduling problem with consumer agents and resource agents. Within the context, all the agents are self-interested aiming at maximising their profits, and have private information, precluding the use of the centralised scheduling approaches that require complete information of all the consumer agents. Therefore, an iterative combinatorial auction mechanism based on a decentralised decision procedure is proposed to generate a collaborative scheduling scheme without violating information privacy. The developed approach adopts flexible bidding strategies to reduce the conflict in resource allocation, and a hybrid auction termination condition is developed to ensure the convergence of the approach while guaranteeing sufficient competition among agents. Experimental results show the developed approach generates high-quality solutions with a small price of anarchy compared with centralised approaches and outperforms the state-of-the-art decentralised scheduling approach in improving social welfare, especially for problems with a large number of consumer agents.

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Section: Experimentation and Results Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An iterative combinatorialauctionmechanism formulti-agentparallel machinescheduling

Liu

Sun

Wang

et al. 2021

International Journal of Production Research

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“…Finally, there are just a few works we are aware of that address the issue of autonomous agents, which is the focus of this paper. One of those is the preliminary study of this paper [52] as well as the paper of Lang et al [20], which analyzes the negotiation of a complex scheduling application incorporating heterogeneous machines, machine operating costs, and nonlinear cost functions. Besides, Liu et al [75] propose a negotiation mechanism for inter-company scheduling with shared resources.…”

Section: Related Workmentioning

confidence: 99%

“…As a final example (cf. ), we consider software procedures and computers in a grid computing or cloud computing scenario. In this case, the jobs are different procedures belonging to different software programs.…”

Section: Problem Descriptionmentioning

confidence: 99%

Collaborative machine scheduling: Challenges of individually optimizing behavior

Lang

Fink

2014

Concurrency and Computation

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SUMMARYCollaborative interorganizational systems is a relevant and promising research domain. When autonomous agents associated with different enterprises negotiate about rival resources, coordination is a major challenge. As agents are driven by self-interest and try to maximize their very own objectives, collaborative planning has to account for some challenges. Collaboration, that is, the participation in a common, shared system, may be profitable for an agent, but cooperation, that is, the pursuing of a common goal, may not be. Additionally, information provided by the agents is a fruit of a poisonous tree because the selfish agents have an incentive to lie strategically, which makes the revealed information unreliable and misleading for a central authority. Moreover, the agents might not be willing to reveal information because of privacy concerns. Consequently, there is a need for sophisticated mechanism design in collaborative systems that facilitate the coordination of non-cooperative agents. This paper deals with rival machine scheduling of one or more homogeneous machines by autonomous agents. Overall objectives are the minimization of the collective total weighted tardiness and Pareto efficient outcomes. We have developed a mediated negotiation protocol drawing on quotas for the acceptance of contract proposals. The protocol ensures that the agents accept sufficient proposals such that they can overcome individual local optima and achieve Pareto superior outcomes. For evaluation purposes, we have conducted several computational experiments. The experiments show that the proposed protocol achieves beneficial outcomes.

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Adaptive Conceding Strategies for Negotiating Agents Based on Interval Type-2 Fuzzy Logic

Zhan¹,

Luo²

2016

Knowledge Science, Engineering and Management

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Design of automated negotiation mechanisms for decentralized heterogeneous machine scheduling

Cited by 23 publications

References 77 publications

An iterative combinatorialauctionmechanism formulti-agentparallel machinescheduling

An iterative combinatorialauctionmechanism formulti-agentparallel machinescheduling

Collaborative machine scheduling: Challenges of individually optimizing behavior

Adaptive Conceding Strategies for Negotiating Agents Based on Interval Type-2 Fuzzy Logic

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